Gay Sex and Digital Media in Beirut: The Social and Erotic Life of Information
Bibliographic record
Abstract
In this dissertation, I examine how queer men in Beirut, Lebanon use sex apps and other social media to create their intimate lives despite the persistence of marginalizing legal, state, and social regulations. Among men, there is a sense that gay sex has become different in the digital age, becoming both more abundant and more ordinary. I argue that gay sex in Beirut is not extraordinary simply because it exists against a set of marginalizing forces, but rather that it is ordinary because of its imbrication in everyday life, habits, and routines. Sex apps are tools for the abundant ordinariness of sex. In my dissertation, I examine the media practices, logics, desires, meanings, categories, and debates queer men in Beirut have developed to live with one another sexually and relationally. What I demonstrate in this ethnography of gay sex in the digital age is that queer politics are not exclusively about resistance, but about the pleasures and struggles of carving out moments for sex, intimacy, and pleasure in an otherwise bounded world. Along with an ethnographic exploration of gay sex and how men talk about it, a central focus of this dissertation is the erotic life of information itself. In digital sex cultures, information plays a central role in the production of desire and sexual possibilities. Information produces feeling, both in the meaning of the words and images, but also in the ritualistic subtleties of how information is shared. The sociality of sex apps, I argue, is fundamentally about exchange as a way of making things happen through the erotic life of information.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.018 | 0.023 |
| Scholarly communication | 0.014 | 0.010 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".